Convert funding, leverage, volatility, basis, liquidation, and market-structure data into probabilistic forecasts, expected ranges, confidence scores, and risk estimates.
Built for institutions that need derivatives market foresight without advisory or execution framing.
Crypto derivatives markets generate continuous data on funding, open interest, liquidations, basis, volatility, skew, and liquidity. Most tools help teams observe the current state of the market. Amonhen adds a probabilistic forecasting layer that estimates how derivatives regimes, volatility conditions, and leverage risk may evolve.
Open interest, funding, basis, and liquidation data are widely available, but they often require manual interpretation.
Funding pressure, liquidation sensitivity, and volatility can shift before spot markets fully reflect the change.
Forward-looking derivatives estimates need clear confidence, coverage, data freshness, and historical performance tracking.
Seven typed forecast surfaces built on derivatives market structure — each delivered with a confidence score and neutral, informational output.
Estimate the probability that funding pressure normalizes, overheats, remains elevated, or changes regime over selected horizons.
Estimate the probability of a liquidation-driven market move under defined reference zones and liquidity conditions.
Estimate expected realized volatility ranges across intraday and medium horizons.
Estimate the probability that futures basis or perpetual premium compresses, widens, or remains stable.
Classify the forecasted derivatives market environment using neutral regime labels.
Estimate price direction probabilities using derivatives market structure as part of the model input.
Score forecast reliability based on data quality, venue coverage, liquidity, volatility regime, model calibration, and horizon.
Every output describes probability, risk, and regime context. Amonhen never states a position to take or an action to execute.
Funding regime forecasts, premium estimates, leverage sensitivity, and liquidation-risk probabilities for major perpetual markets.
Forward-looking basis and premium estimates for dated futures and cash-and-carry monitoring workflows.
Realized volatility forecasts and implied-versus-forecast volatility context for institutional volatility workflows.
Cross-venue derivatives regime estimates using funding, open interest, liquidity, liquidation, and volatility data where coverage supports model output.
When data coverage is insufficient, Amonhen downgrades or suppresses forecast confidence rather than overstating precision.
Every output is a typed object with a defined horizon, an example estimate, and explicit confidence support.
| Forecast object | Description | Example horizon | Example output | Confidence |
|---|---|---|---|---|
| Funding regime forecast | Probability of funding pressure normalizing, overheating, or changing regime | 4h · 24h · 7d | Normalization probability 58% | Yes |
| Liquidation cascade probability | Probability of liquidation-driven market stress | 1h · 4h · 24h | Cascade probability: elevated | Yes |
| Realized volatility forecast | Expected realized volatility range | 1d · 7d · 30d | 42% to 51% annualized | Yes |
| Basis / premium forecast | Probability basis or premium compresses, widens, or remains stable | 24h · 7d · 30d | Compression probability 57% | Yes |
| Derivatives regime estimate | Forecasted derivatives market structure label | 4h · 24h · 7d | Balanced leverage · leverage unwind · volatility expansion | Yes |
| Forecast attribution | Key drivers behind forecast output | All horizons | Funding pressure · open interest · liquidity depth · liquidation history · premium | Yes |
Amonhen emphasizes probability, risk, and regime context rather than execution instructions.
Neutral, model-generated scenarios — each with a probability, an expected volatility range, a confidence level, and the main drivers behind it.
Surface neutral risk estimates, volatility outlooks, and forecast confidence inside market-monitoring and client-facing experiences.
Use forecast distributions, funding regime estimates, volatility forecasts, and liquidation-risk probabilities as decision-support inputs.
Monitor forward-looking volatility, liquidity, funding, and leverage conditions across supported markets.
Use expected volatility ranges, basis estimates, and scenario probabilities as inputs for risk-monitoring and product analysis workflows.
Track derivatives regime changes, confidence downgrades, and model-generated stress estimates across venues and assets.
Amonhen delivers informational, model-generated estimates. Your teams decide what to do with them.
Amonhen tracks derivatives forecasts against realized outcomes and supports historical forecast archives, calibration metrics, coverage checks, confidence scoring, data freshness awareness, and forecast attribution.
Predicted probabilities are measured against realized frequencies.
A durable record of every forecast ever issued.
Every forecast carries a calibrated confidence level.
Estimates are withheld where data coverage is insufficient.
Forecasts expose the recency of their input data.
Each output is traceable to the drivers behind it.
{ "market": "ETH-PERP", "module": "derivatives_forecasts", "horizon": "24h", "funding_regime_forecast": { "status": "elevated", "normalization_probability": 0.58 }, "liquidation_cascade_probability": "medium", "realized_volatility_forecast": { "status": "elevated", "range_annualized": { "lower": 0.48, "upper": 0.62 } }, "basis_premium_forecast": { "direction": "stable_to_widening", "probability": 0.52 }, "confidence": "medium", "regime": "volatility_expansion", "disclaimer": "model_generated_informational_estimate" }
Amonhen transforms funding, leverage, volatility, liquidation, basis, and market-structure data into probabilistic forecasts and confidence-scored risk estimates.